Fraud Analytics

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Fraud Analytics

Fraud detection is a concept used in many industries including banking and financial sectors, insurance, government agencies and law enforcement, and more. Fraud attempts have seen a drastic increase in recent years, making fraud detection more important than ever.

In banking, fraud can involve using stolen credit cards, forging checks, misleading accounting practices, etc. In insurance, 25% of claims contain some form of fraud, resulting in approximately 10% of insurance payout dollars.

A new approach being used for fraud prevention and detection involves the examination of patterns in the actual data. The rationale is that unexpected patterns can be symptoms of possible fraud.


In Insurance Sector

  • Detect more fraudulent activity
  • Lower loss-adjustment expenses
  • Gain a greater competitive advantage
  • Prevent fraud losses before settlement

In Banking

  • To avoid Risk of losing customers
  • To avoid Financial losses
  • To avoid Fraud incidents

In Healthcare

  • Highlight billing for medically unnecessary tests
  • Highlight excessive use of high risk DRGs ( “ Diagnosis-Related Groups ” )
  • Identify excessive billing by a single physician
  • Report entries against authorization records for new or terminated employees

In Telecom

  • Provide future-proof detection techniques
  • Guard against habitual offenders
  • Ensure that pre-paid service is truly risk free
  • Launch profitable IP-based services